RABIES | fMRI preprocessing pipeline and analysis tools | Computer Vision library

by CoBrALab Python Version: 0.5.1 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | RABIES Summary

RABIES is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning, Docker applications. RABIES has no bugs, it has no vulnerabilities, it has build file available and it has low support. However RABIES has a Non-SPDX License. You can install using 'pip install RABIES' or download it from GitHub, PyPI.

RABIES is an open source image processing pipeline for rodent fMRI. It conducts state-of-the-art preprocessing and confound correction, and supplies standard resting-state functional connectivity analyses. Visit our documentation at

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Quality

Security

License

Reuse

Support

RABIES has a low active ecosystem.

It has 21 star(s) with 10 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 33 open issues and 88 have been closed. On average issues are closed in 90 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of RABIES is 0.5.1

Quality

RABIES has 0 bugs and 0 code smells.

Security

RABIES has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

RABIES code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

RABIES has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

RABIES releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

It has 7050 lines of code, 180 functions and 38 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed RABIES and discovered the below as its top functions. This is intended to give you an instant insight into RABIES implemented functionality, and help decide if they suit your requirements.

Run the interface
Compute the Least Squares estimate
Compute butterworth for each signal
Run IICA_AROMA
Plot the scan diagnostic
Plots a grayplot of the time series
Calculate the percent threshold of a voxels
Plot masked image
Register the MNI - T1 Voxel template
Computes the masks for the given table
Slice the timings of an image
Function to classify the ICs
Visualize the template information
Runs the motion estimation
Argument parser
Runs the interface
Plot temporal features
Run the ANTsImage
Create a time - series model from a melodic mixogram
Run the plot
Generate classification plot
Extracts the feature spectrum from the input files
Run MELODIC
Preprocess the input files
Reads preproc_data files
Run NIPype

Get all kandi verified functions for this library.

RABIES Key Features

No Key Features are available at this moment for RABIES.

RABIES Examples and Code Snippets

No Code Snippets are available at this moment for RABIES.

Community Discussions

Trending Discussions on RABIES

How to create 'update' using multiple 'set' methods

Pivoting a join table

Are the answers of this C++ quiz correct?

Fetch rows with maximum length of string in another column in Postgres

QUESTION

How to create 'update' using multiple 'set' methods

Asked 2021-Dec-06 at 11:57

Synopsis: I'm trying to create an SQL update using jOOQ

...

ANSWER

Answered 2021-Dec-06 at 11:57

You ran into this problem: Reference is ambiguous with generics

Fixing your query

It's always a good idea to attach data types with your jOOQ expressions. In your particular case, you can work around the problem by specifying things like:

Source https://stackoverflow.com/questions/70215919

QUESTION

Pivoting a join table

Asked 2021-Mar-08 at 23:09

I have three tables set up like below

...

ANSWER

Answered 2021-Mar-08 at 23:09

You can use conditional aggregation:

Source https://stackoverflow.com/questions/66538208

QUESTION

Are the answers of this C++ quiz correct?

Asked 2021-Jan-06 at 09:18

In the university I had a quiz today. The quiz is over but I can't understand some of its questions are their correct answers.

Note: I am not asking this to solve my quiz. Quiz is over I am just confused in some questions.

Question 1:

Consider the following variable declarations:

...

ANSWER

Answered 2021-Jan-06 at 09:12

3 errors in question 2:

missing ( ) around the if condition
in the second part of the if condition there must be double ==
{ } are missing

To be a valid code it must be set like this:

Source https://stackoverflow.com/questions/65592913

QUESTION

Fetch rows with maximum length of string in another column in Postgres

Asked 2020-Jun-29 at 20:51

I have following table in postgres11

...

ANSWER

Answered 2020-Jun-29 at 20:48

distinct on always return only one row per group - if the order by clause is not deterministic, then you get a random row out of the ties.

If you want to allow ties, then you can use rank() and a subquery instead:

Source https://stackoverflow.com/questions/62646386

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install RABIES

You can install using 'pip install RABIES' or download it from GitHub, PyPI.
You can use RABIES like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

RABIES is under continuous development to keep up with evolving demand and ongoing research. We welcome suggestions for improvements using the Github issue system. If you're interested in contributing code, you can reach out on the Github discussion and we welcome contributions as pull requests.

Find more information at: